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Article Processes in the Unsaturated Zone by Reliable Estimation: Indications for Management from a Sandy Soil Experimental Field in Central Italy

Lucio Di Matteo * , Alessandro Spigarelli and Sofia Ortenzi

Dipartimento di Fisica e Geologia, Università degli Studi di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy; [email protected] (A.S.); sofi[email protected] (S.O.) * Correspondence: [email protected]; Tel.: +39-0755-849-694

Abstract: Reliable data are essential for achieving sustainable water management. In this framework, the performance of devices to estimate the volumetric moisture content by means dielectric properties of soil/water system is of increasing interest. The present work evaluates the performance of the PR2/6 soil moisture profile probe with implications on the understanding of processes involving the unsaturated zone. The calibration at the laboratory scale and the validation in an experimental field in Central Italy highlight that although the shape of the moisture profile is the same, there are essential differences between soil moisture values obtained by the calibrated equation and those obtained by the manufacturer one. These differences are up to 10 percentage points for fine-grained containing iron oxides. Inaccurate estimates of soil moisture content do not help with understanding the soil water dynamic, especially after rainy periods. The sum of antecedent soil moisture conditions (the Antecedent Soil moisture Index (ASI)) and rainfall related to different stormflow can be used to define the threshold value above which the runoff significantly  increases. Without an accurate calibration process, the ASI index is overestimated, thereby affecting  the threshold evaluation. Further studies on other types of materials and in different climatic Citation: Di Matteo, L.; Spigarelli, A.; conditions are needed to implement an effective monitoring network useful to manage the soil water Ortenzi, S. Processes in the and to support the validation of remote sensing data and hydrological soil models. Unsaturated Zone by Reliable Soil Water Content Estimation: Keywords: soil moisture; PR2/6 probe; infiltration; soil water management Indications for Soil Water Management from a Sandy Soil Experimental Field in Central Italy. Sustainability 2021, 13, 227. 1. Introduction https://doi.org/10.3390/su13010227 In the effort to achieve most of the United Nation (UN) Sustainable Development Received: 12 December 2020 Goals (SDGs), it is necessary to move towards a sustainable use and management of the Accepted: 25 December 2020 soil-water system [1]. For achieving sustainable water management, the monitoring of soil Published: 29 December 2020 moisture content is mandatory in the understanding of processes involving the unsaturated zone (e.g., infiltration, migration of pollutants, etc.) [2]. As reported by Vanclooster [3], Publisher’s Note: MDPI stays neu- the monitoring is linked to the modeling of soil processes and space-based environmental tral with regard to jurisdictional claims monitoring systems can give benefits, such as rapid and effective adaptation of the water in published maps and institutional sector [4]. In this framework, sustainable soil and water management objectives require affiliations. reliable data. According to Escorihuela and Quintana–Seguí [5], reliable soil moisture data are essential in the Mediterranean region because they affect the characteristics of land processes such as droughts and floods. The ongoing climate change affecting this area

Copyright: © 2020 by the authors. Li- decreased rainfall during the recharge period (autumn to spring period, e.g., [6–8]) and censee MDPI, Basel, Switzerland. This intensified extreme rainfall events [9]. As recently reported by Mimeau et al. [10], future article is an open access article distributed scenarios indicate a further change of precipitation patterns in the coming years. These under the terms and conditions of the changes are associated with an intensification of extreme rainfall events alternating with Creative Commons Attribution (CC BY) long periods of drought, increasing the on land with progressive degradation license (https://creativecommons.org/ processes affecting soil productivity, irrigation, recharge, etc. [11]. The moni- licenses/by/4.0/).

Sustainability 2021, 13, 227. https://doi.org/10.3390/su13010227 https://www.mdpi.com/journal/sustainability Sustainability 2021, 13, 227 2 of 15

toring of the soil-water system is crucial in the efficiency of water use, while also improving the agricultural sustainability [12]. Soil moisture can be obtained by direct methods (thermo-gravimetric laboratory method, [13]) or indirect methods, most of which are based on the measurement of the dielectric properties of the soil-water system. The two methods are used locally, have advantages and disadvantages, and are complementary to each other. The gravimetric method is the standard technique to measure the gravimetric water content (θg). It is also useful to calibrate the estimates of the indirect methods. It requires the soil sampling (destructive method), is time-consuming, and cannot be used for the monitoring in the field [14,15]. Indirect methods allow real-time and continuous monitoring of the volumetric water content (θ) and are more and more used in the latest years. Several instruments are available with different accuracy, costs (including the maintenance), the difficulty of installation, and response time [16]. Compared to the Time Domain Reflectometry (TDR), the Capacitance and Frequency Domain Reflectometry (FDR) allow, by means of the profile probe (PP), the estimation of spatial-temporal evolution of θ [17–23]. Moreover, PP can contribute to the implementation of an integrated monitoring system, also aiming to map the spatial variation of the soil water content coupled with other electromagnetic methods, such as the Ground Penetrating Radar, GPR [24,25]. Field investigations also help the calibration and validation of remote sensing data, enhancing the understanding of processes at large scales [26,27]. The quality of locally monitored data is the basis for the re-analysis of the soil water content data from satellites [28]. Although the using of capacitance and FDR profile probes is increasing, the calibration problem and performance of the instrumentations cannot be neglected, especially when they are to be applied in large sites [17,23,29–35]. In other words, the use of manufacturer equations to convert the electromagnetic properties of soils into θ may lead to incorrect assessments of the soil moisture content, with inevitable effects on soil water management and in the understanding of processes occurring in the unsaturated zone [23,36,37]. In this framework, the present work aims to contribute in evaluating the performance of the PR2/6 soil moisture profile probe with implications on devices operating at a frequency of 100 MHz. An experimental field in Central Italy is selected and the monitored data are presented and discussed, taking into account the equation used to estimate the soil water content, the antecedent rainfalls, and the modeled parameters of the unsaturated soil.

2. Materials and Methods 2.1. Experimental Field and Soil Characteristics For the study, an experimental plot 18 m2 wide was selected. The site is located in Central Italy in the left bank of the Tiber River alluvial plain (43◦07033.60” N–12◦26004.76” E, Figure1a), where a fine-grained soil widely outcrops (soil S B). According to the USDA (United States Department of Agriculture) classification, this soil is a loamy- deriving from the of marly-calcareous-siliceous rocks (Flysch) widely outcropping in the Tiber River catchment (the mineralogical composition and organic matter content is shown in Table1). The lithological model of the site has been reconstructed with the GPR sur- vey [25], with the Dynamic Probe Super Heavy test (DPSH) and with sampling at different depths (0.15, 0.45, 0.60, 0.80, and 0.95 cm) aiming to obtain the main physical parameters of the soil (Figure1b). The site is equipped by a weather station (rainfall and temperature) managed by the Servizio Idrografico della Regione Umbria (Figure1a) and by a PR2/6 profile probe (Delta-T Devices Ltd., Cambridge, UK), which constitutes an integrated monitoring system. The area is characterized by a mean precipitation of about 860 mm/year and mean annual temperature of 14.5 ◦C (1992–2019 period). As shown in Figure1c, the of tends to increase with depth. Within the in- vestigation range of the infiltration process (in the first-meter depth), there is homogeneous 3 loose sand with dry unit weight (γd) of about 14.33 kN/m and void index (e) of 0.82 (data Sustainability 2021, 13, 227 3 of 15

obtained on the soil samples collected from S6 and S5). These are young alluvial sediments related to the two important floods of the Tiber River occurred in November 2005 and in November–December 2010. The geotechnical characteristics of soil SB, together with some other non-plastic soils (sands and loamy sands of different nature), are shown in Table1. As presented in the introduction section, to check the performance of measurements by indirect methods, the comparison of empirical equations to estimate θ values on similar materials can be useful. The results of this analysis will be presented in Section 3.1.

Figure 1. (a) Location of the experimental field; (b) sketch of the survey site with the instruments used for the reconstruction of the geological model and for the monitoring of the infiltration process

(DPSH = Dynamic Probe Super Heavy; S5 and S6 = sampling sites, P1 = PR2/6 profile probe); (c) lithological section with the details of the DPSH1 profile.

1

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Table 1. Geotechnical and mineralogical properties of soils. OM = Organic Matter according to ASTM standard [38]. Particle size distribution according to ASTM standard [39].

Grain Size (%) OM Name Source Origin Mineralogy Sand (%) Nera River Carbonates with subordinate Soil S [23] 95.25 3.45 1.30 0.37 A (Central Italy) minerals (muscovite, gypsum) Flyschoid sand Tiber River (, calcite, albite, chlorite Soil S [23] 82.41 14.59 3 1.53 B (Central Italy) muscovite, pyrite, and orthoclase) Unpublished Paglia River Soil S 94.61 3.90 1.49 0.23 - C data (Central Italy) England and Soil 1 [30] 99.30 0 0.70 0.36 Quartz Northern Ireland England and Soil 2 [30] 97.20 2.40 0.40 1.07 Quartz Northern Ireland England and Quartz Soil 3 [30] 66.20 1.10 1.03 1.03 Northern Ireland (>5% iron oxide/) England and Soil 4 [30] 95.50 4.20 0.30 2.06 Quartz Northern Ireland

2.2. Monitoring of the Volumetric Water Content and Infiltration 2.2.1. The PR/2 Profile Probe The PR2/6 capacitance profile probe allows the estimation of the soil volumetric water content (θ) at different depths. The device requires the installation of an access tube of 1.10 m length into the soil. A 9-volt battery generates a signal of 100 MHz (similar to FM radio), which is applied to six pairs of stainless steel rings placed at different depths (0.10, 0.20, 0.30, 0.40, 0.60, and 1.00 m). An electromagnetic field extends all around the device (Figure2 ) and a data logger records the voltage output (V), which is converted into the √ square root of the dielectric constant ( ε) by a six-order polynomial equation (Equation (1), [40]). The volumetric water content is then obtained by a soil calibration equation (Equation (2)), which contains two parameters, a0 (soil offset) and a1 (slope), as proposed by [41]. The dielectric constant (ε) obtained by the PR2/6 probe is the sum of soil real (ε’) and imaginary (ε”, dielectric loss) permittivity. It is known that for devices working at low frequencies (<1 GHz), the ε” can be affected by the water salinity and therefore influencing the estimates of θ. This problem cannot be neglected for effluent waters with electrical conductivity values higher than 1500–5000 µS/cm [42,43]. According to the PR2/6 manual [40], the probe has a very low intrinsic sensitivity to the salinity of effluent water when it is of an order of magnitude lower than that reported by the above reference studies. In these cases, the accuracy of measurements mainly depends on the proper choice of parameters a0 and a1 of Equation (2): in general, the manufacturer suggests to set a0 = 1.6 and a1 = 8.4 for mineral soils. The same parameters are suggested for other commercially available electromagnetic devices such as SM200, SM300, and Theta Probe ML2x. All these probes are produced by the Delta-T Devices, work at the same frequency of PR2/6 (100 MHz), and θ values are estimated from voltage outputs of sensors [44]. Sustainability 2021, 13, 227 5 of 15

In this work, the column test has been used for the calibration of parameters a0 and a1 as already proposed by other studies [23,37]. Figure2 summarizes the step-by-step θ procedure used for calibrating√ the PR2/6 probe. By using Equation (2), actual values are computed and related to ε values for obtaining the best a0 and a1 parameters for the investigated soil. √ ε = 1.125 − 5.53V + 61.17V2 − 234.42V3 + 413.56V4 − 356.68V5 + 121.53V6 (1) Sustainability 2021, 13, x FOR PEER REVIEW 5 of 15 √ ε = a0 + a1θ (2) where γd θg = Mw/Mθs =(Massθg· of water/Mass of solids); (3) γw θ = M /M (Mass of water/Mass of solids); g wγd = Drys unit weight of soil (kN/m3); 3 γd = Dry unit weight of soil (kN/m ); γw = Unit weight of water (kN/m3). 3 γw = Unit weight of water (kN/m ).

Figure 2. 2. Step-by-stepStep-by-step procedure procedure for for the the calibration calibration of PR2/6 of PR2/6 probe probe used used in this in research. this research. The The compaction procedure used to compact soil in the column refers toto [[23].23].

2.2.2. Double Double Ring Infiltrometer Infiltrometer The Double RingRing InfiltrometerInfiltrometer (DRI) (DRI) is is a standardizeda standardized technique technique [45 ][45] used used to estimate to esti- matethe infiltration the rate of rate water of inwater fine-grained in fine-g soils.rained The soils. instrument The instrument is composed is composed of two steel of tworings steel of different rings of diameters:different diameters: in this study, in this the study, inner ringthe inner is 30 cmring wide is 30 while cm wide the outerwhile ring the outeris 60 cm. ring By is using60 cm. a MariotteBy using bottle,a Mariotte the volume bottle, ofthe water volume needed of water to keep needed the water to keep level the in waterthe inner level rings in the constant inner (constantrings constant head) (const is measuredant head) over is time. measured The water over passingtime. The from water the inner ring to the soil during a time-step (∆t) represents the infiltration rate (i, Equation (4)). passing from the inner ring to the soil during a time-step (Δt) represents the infiltration The steady-state infiltration can be assumed as the saturated of rate (i, Equation (4)). The steady-state infiltration can be assumed as the saturated hy- the soil (ks), even if the value obtained may be influenced by entrapped air in the voids, draulic conductivity of the soil (ks), even if the value obtained may be influenced by en- biological activity, size of rings, etc. [46]. trapped air in the voids, biological activity, size of rings, etc. [46]. V𝑉 (4) i 𝑖== (4) π𝜋·r∙𝑟2·∆∙𝛥t 𝑡 where: where: i = infiltration rate (cm/s); Vi = = infiltrationvolume of rateadded (cm/s); water (cm3) in each time-step (Δt); 3 ΔVt == volumetime step of (s); added water (cm ) in each time-step (∆t); r∆ =t =radius time stepof the (s); inner ring (cm).

2.3. The Soil Water Characteristic Curve (SWCC) Most of the information for the understanding of infiltration processes within the unsaturated soils is contained in the Soil Water Characteristic Curve (SWCC). The SWCC relates the matric suction (the difference between pore air pressure, ua, and , uw) and θ [47]. As reported by Lu and Likos [48], direct measurements of the matric suction are time-consuming, and often only a few data points of the SWCC are obtained [49]. In this work to reconstruct the SWCC of the soil SB outcropping in the ex- perimental field, “The Soil Water Characteristics software (version 6.02.75)” is used Sustainability 2021, 13, 227 6 of 15

r = radius of the inner ring (cm).

2.3. The Soil Water Characteristic Curve (SWCC) Most of the information for the understanding of infiltration processes within the unsaturated soils is contained in the Soil Water Characteristic Curve (SWCC). The SWCC relates the matric suction (the difference between pore air pressure, ua, and pore water pressure, uw) and θ [47]. As reported by Lu and Likos [48], direct measurements of the matric suction are time-consuming, and often only a few data points of the SWCC are obtained [49]. In this work to reconstruct the SWCC of the soil SB outcropping in the experimental field, “The Soil Water Characteristics software (version 6.02.75)” is used (download page: https://hrsl.ba.ars.usda.gov/soilwater/Index.htm). This software, which has been developed by the USDA [50], estimates several hydrological soil properties based on the texture class, fraction, organic matter, salinity, and compaction (dry unit weight). In detail, the program–by using the model developed by [51]–allows the estimation of the matric suction and some other essential parameters (residual volumetric water content, θr, and saturated volumetric water content, θs) that are useful to estimate the suction (σs). As reported by Lu and Likos [48], σs can be expressed in terms of normalized volumetric water content (or effective degree of saturation, Se) and matric suction (Equation (5)):

s θ − θr σ = − ·(ua − uw) = −Se·(ua − uw) (5) θs − θr where: σs = suction stress (kN/m2) θ = volumetric water content (m3/m3) 3 3 θr = residual volumetric water content (m /m ) 3 3 θs = saturated volumetric water content (m /m ) 2 ua = pore air pressure (kN/m ) 2 uw = pore water pressure (kN/m ) 2 (ua − uw) = matric suction (kN/m ) 3 3 Se = effective degree of saturation (m /m ).

3. Results 3.1. Calibration of PR2/6 Probe on Soil SB and Comparison with Other Sands The step-by-step procedure presented in Figure2 allowed the obtaining of reliable calibration curves for accurate estimates of θ values by the PR2/6 profile probe, an essential step before using the device in the field. Figure3 shows the calibration curves with parameters a0 and a1 of Equation (2) for the different sands listed in Table1, also referring to previous published data [23,30]. Figure3 also shows the data of a new sand (soil S C) collected in a quarry located in the Paglia River alluvial plain, Central Italy (42◦44014.92” N–12◦06038.13” E, [52]). It is interesting to point out that the equations differ from that suggested by the manufacturer, which tends to overestimate the θ values. Sustainability 2021, 13, x FOR PEER REVIEW 7 of 15 Sustainability 2021, 13, 227 7 of 15

FigureFigure 3. 3. CalibrationCalibration curves curves for for sandy sandy soil soilss of of different different nature nature (the (the main main characteristics characteristics of of soils soils are are inin Table Table 1).1). θθ valuesvalues are are obtained obtained on on soil soil samples samples byby the the gravimetric gravimetric method method using using Equation Equation (3), (3), followingfollowing the the procedure procedure in in Figure Figure 2.2. (1) (1) data data obta obtainedined with with the the PR2/6 PR2/6 probe probe (taken (taken from from [23]); [ 23 (2)]); (2) unpublished data obtained with the PR2/6 probe (soil from Paglia River, Central Italy); (3) data unpublished data obtained with the PR2/6 probe (soil from Paglia River, Central Italy); (3) data obtained with the Theta probe (taken from [30]). PR2/6 and Theta probes work at the same fre- obtained with the Theta probe (taken from [30]). PR2/6 and Theta probes work at the same frequency quency (100 MHz), and θ values are estimated from voltage outputs of sensors. (100 MHz), and θ values are estimated from voltage outputs of sensors.

3.2. Soil Water Characteristic Curve of Soil SB and Infiltration Test 3.2. Soil Water Characteristic Curve of Soil SB and Infiltration Test TheThe Soil Soil Water Water Characteristics Characteristics software software ha hass been been used used to to model hydrological soil soil B propertiesproperties of of soil soil S SB outcroppingoutcropping in in the the experimental experimental field. field. The The input input parameters parameters which which hashas been been set set into into the the program program are: are: • • sand andsand clay and fraction clay fraction of 82% andof 82% 3%, and respectively 3%, respectively (Table1); (Table 1); • • organicorganic matter contentmatter content of 1.53% of (Table 1.53%1); (Table 1); • • electricalelectrical conductivity conductivity of the effluent of the effluent fluids, 440 fluids,µS/cm 440 [μ23S/cm]; [23]; • dry unit weight (14.33 kN/m3). • dry unit weight (14.33 kN/m3). Figure 4a shows the SWCC and the hydraulic conductivity curve of soil SB. The Figure4a shows the SWCC and the hydraulic conductivity curve of soil S B. The modeled residual volumetric water content, θr, and saturated volumetric water content, modeled residual volumetric water content, θr, and saturated volumetric water content, θs, were 3.0% and 44.9%, respectively. The estimated θs agrees with that calculated by θ , were 3.0% and 44.9%, respectively. The estimated θ agrees with that calculated by applyings the unit-weight relationship (Equation (6)), whichs provides a value of 45.5%. In applying the unit-weight relationship (Equation (6)), which provides a value of 45.5%. In the computation, the following data have been considered: γd = 14.33 kN/m3; e = 0.82; γ 3 the computation, the following data have3 been considered: d = 14.33 kN/m ; e = 0.82; specific gravity, Gs = 2.63; γw = 9.81 kN/m . 3 specific gravity, Gs = 2.63; γw = 9.81 kN/m . γ ∙e γd·e θsθ== (6)(6) GGs·γ∙ wγ

The modeled saturated hydraulic conductivity (ks) resulted in 3.4 × 10−3 cm/s (Figure 4a). Figure 4b shows the result of the DRI test carried out in the field at the end of July 2018. The initial θ value in the first 30 cm depth was about 5%. The infiltration curve is described by the Horton equation [53] and approaches to quasi-steady-state conditions after about 150 min, reaching a value of about 8.0 × 10−3 cm/s. Although the enclosure of air bubbles in the voids during infiltration prevents maximum saturation, the ks value Sustainability 2021, 13, 227 8 of 15

−3 The modeled saturated hydraulic conductivity (ks) resulted in 3.4 × 10 cm/s (Figure4a ). Figure4b shows the result of the DRI test carried out in the field at the end of July 2018. The initial θ value in the first 30 cm depth was about 5%. The infiltra- Sustainability 2021, 13, x FOR PEER REVIEWtion curve is described by the Horton equation [53] and approaches to quasi-steady-state8 of 15

conditions after about 150 min, reaching a value of about 8.0 × 10−3 cm/s. Although the enclosure of air bubbles in the voids during infiltration prevents maximum saturation, the ks value obtained by the infiltrometer is of the same order of magnitude of the ks predicted obtained by the infiltrometer is of the same order of magnitude of the ks predicted by the by the SWC software. SWC software.

Figure 4. Hydraulic properties of soil SB outcropping in the experimental field. (a) Soil Water Characteristic Curve Figure 4. Hydraulic properties of soil S outcropping in the experimental field. (a) Soil Water Characteristic Curve (SWCC) (SWCC) and hydraulic conductivity curvesB as modeled by the Soil Water Characteristic software [50]. (b) Infiltration rate b obtainedand hydraulic with the conductivityDRI test. curves as modeled by the Soil Water Characteristic software [50]. ( ) Infiltration rate obtained with the DRI test. 3.3. Precipitation Analyses and Soil Water Profiles 3.3.The Precipitation monitoring Analyses of the spatial-temporal and Soil Water Profiles variations of soil water content with depth is importantThe in monitoring different practical of the spatial-temporal applications (hydrological, variations of soilhydrogeological, water content and with pedo- depth is logical).important To check in different the response practical of applications the PR2/6 probe, (hydrological, the soil hydrogeological,water profile dynamic and pedologi- has beencal). analyzed To check during the response April–May of the 2018. PR2/6 Figu probe,re 5a shows the soil the water daily profile rainfall dynamic and tempera- has been tureanalyzed data recorded during in April–May the period 2018. by the Figure weather5a shows station the dailylocated rainfall less than and temperature70 m from the data experimentalrecorded in site the (Figure period by1a). the In weather detail, Ma stationrch 2018 located experienced less than very 70 m high from precipitations, the experimental whichsite (Figurewere found1a). Into detail,be more March than 2018 three experienced times higher very than high the precipitations, historical mean which (Figure were 5b).found In the to subsequent be more than months, three rainfall times higherdata were than in theline historical with the historical mean (Figure mean,5b). with In thea notsubsequent negligible months,increase rainfall also found data were in May. in line During with the the historical observation mean, period with a not(late negligible win- ter-springincrease months) also found the in air May. temperature During the gradua observationlly increased, period except (late winter-spring for the two months)rainy pe- the riodsair of temperature March and gradually May 2018. increased, In this framework, except for thethe twotemp rainyoral periodsvariations of Marchof soil andwater May content2018. with In this depth framework, allow the the understanding temporal variations of processes of soil during water wetting content and with drying depth pe- allow riods.the Figure understanding 5a also shows of processes the location during of wetting four selected and drying comprehensive periods. Figure water5a also content shows measurementsthe location oftaken four before selected and comprehensive after importan watert meteorological content measurements events. In takenorder beforeto have and accurateafter important water content meteorological data, each events.measure In has order been to repeated have accurate at least water seven content times data,by set- each tingmeasure the PR2/6 has datalogger been repeated with at both least calibrat seven timesed parameters by setting and the PR2/6manufacturer datalogger ones with (min- both eralcalibrated soil). parameters and manufacturer ones (mineral soil). Sustainability 2021, 13, x FOR PEER REVIEW 9 of 15 Sustainability 2021, 13, 227 9 of 15

FigureFigure 5. 5.Daily Daily rainfall rainfall and and temperature temperature data data in the in experimental the experiment fieldal (Pontefield (Ponte Felcino Felcino weather weather station 2station probe) (2a ).probe) Monthly (a). rainfallMonthly data rainfall compared data compared to the historical to the meanhistorical (b). mean (b).

FigureFigure6 6 shows shows the the selected selected soil soil moisture moisture profiles. profiles. Following Following we we present present the the results results obtainedobtained by by setting setting the the HHD HHD datalogger datalogger of of the the PR2/6 PR2/6 probe probe with with the the calibrated calibrated parameters, parame- movingters, moving the discussion the discussion about theabout differences the differ obtainedences obtained with the with manufacturer’s the manufacturer’s parameters pa- for mineral soils to the next section. rameters for mineral soils to the next section. The first measurement refers to 26 April 2018 (Supplementary Materials), after about The first measurement refers to 26 April 2018 (supplementary), after about two two weeks from the end of a very high rainfall period (Figure6a). Due to the effect of the weeks from the end of a very high rainfall period (Figure 6a). Due to the effect of the an- antecedent rainfalls (about 250 mm in two months), the moisture profile shows the typical tecedent rainfalls (about 250 mm in two months), the moisture profile shows the typical shape of a wetting front moving downwards e.g., [54]. The low values in the shallow shape of a wetting front moving downwards e.g., [54]. The low values in the shallow zone (the first 30 cm depth) are also due to the effect of the evapotranspiration (the air zone (the first 30 cm depth) are also due to the effect of the evapotranspiration (the air temperature increased of about 10 ◦C in the week before the measurement). The succession temperature increased of about 10 °C in the week before the measurement). The succes- of rainy and dry periods in the following weeks introduced a lot of disturbing effects on sion of rainy and dry periods in the following weeks introduced a lot of disturbing ef- the soil water profile. The precipitations occurred at the beginning and middle of May fects on the soil water profile. The precipitations occurred at the beginning and middle increased the volumetric water content in the first 30 cm depth of about 12 percentage of May increased the volumetric water content in the first 30 cm depth of about 12 per- points (Figure6b,c). The water distribution in the first-meter depth has gradually assumed centage points (Figure 6b,c). The water distribution in the first-meter depth has gradu- a constant profile with an effective degree of saturation (Se) of about 36% (Figure6g). As shownally assumed in Figure a 6constantd, after few profile days with of no an rainfall–coupled effective degree with of saturation a rise of evapotranspiration (Se) of about 36%. phenomenaAs shown in linked Figure to 6d, the increaseafter few in days temperature–the of no rainfall–coupled water profile with tended a rise to of re-assume evapotran- a shapespiration similar phenomena to that recorded linked to on the 12 Mayincrease 2018. in Figure temperature–the6i–l also display water the profile matric tended suction to profilesre-assume during a shape the samesimilar observation to that recorded period, on as obtained12 May 2018. from Figure the SWC 6a,d software. also display In each the measurement,matric suction the profiles matric during suction the decreases same observation with depth withperiod, maximum as obtained changes from in the the SWC first 30software. cm as affected In each by measurement, meteo-climatic the conditions. matric suction For instance, decreases between with depth 26 April with and maximum 12 May, achanges mean decrease in the first of 15030 cm kPa as is affected observed by in meteo-climatic the shallow zone. conditions. For instance, between 16 April and 12 May, a mean decrease of 150 kPa is observed in the shallow zone. Sustainability 2021, 13, x FOR PEER REVIEW 10 of 15 Sustainability 2021, 13, 227 10 of 15

Figure 6. ProfilesProfiles of volumetric water water content content ( (θθ), effective degree of saturation (Se), and matric matric suction suction (u (uaa-u−w)u forw) forsoil soil SB. TheSB. Thedashed dashed red redand and blue blue curves curves are are based based on on estimates estimates of of θθ byby using using calibrated calibrated parameters parameters (a o == 1.9 1.9 and and a 11 == 10.6) 10.6) and manufacturer parameters (ao == 1.6 1.6 and and a a11 == 8.4), 8.4), respectively. respectively. (a (a,e,e,i,)i )Profiles Profiles recorded recorded on on 26 26 April April 2018; 2018; ( (bb,,ff,,jj)) 12 12 May May 2018; 2018; (c,g,k) 16 May 2018; (d,h,l) 20 May 2018.

4. Discussions 4. Discussion The performed analysis confirms that there is no unique relationship between die- The performed analysis confirms that there is no unique relationship between di- lectric properties of the medium (√ε)√ and θ, even when the same instrument is used on similarelectric materials properties (e.g., of thenon-plastic medium soils). ( ε) Most and θ of, eventhe sands when analyzed the same here instrument tend to align is used on on similar materials (e.g., non-plastic soils). Most of the sands analyzed here tend to the calibration curve having a0 = 1.7 and a1 = 9.5, which differs from that of the manufac- align on the calibration curve having a = 1.7 and a = 9.5, which differs from that of the turer (mineral soils, a0 = 1.6 and a1 = 8.4).0 For this sand1 types (mainly composed by quartz and/ormanufacturer calcium (mineral carbonate, soils, Table a0 = 1) 1.6 the and use a1 of= the 8.4). manufacture For this sand parameters types (mainly leads composed to a not by quartz and/or calcium carbonate, Table1) the use of the manufacture parameters leads excessive overestimation of θ values from 2 to 5 percentage points. In contrast, SB to a not excessive overestimation of θ values from 2 to 5 percentage points. In contrast, sands-coming from the experimental field-shows the highest parameters (a0 = 1.9 and a1 = 10.6),SB sands-coming which in turn from give the θexperimental values from 5 field-shows to 10 percentage the highest points parameters lower than (a 0those= 1.9 esti- and a = 10.6), which in turn give θ values from 5 to 10 percentage points lower than those mated1 by using the manufacturer’s parameters. The probe calibration is always neces- estimated by using the manufacturer’s parameters. The probe calibration is always nec- sary, but it is particularly important for capacitance probes working at low frequency, essary, but it is particularly important for capacitance probes working at low frequency, especially when used in a medium having high iron content. The iron content affects the especially when used in a medium having high iron content. The iron content affects the imaginary component (ε”) of the dielectric constant of the soil/water system [55]. For imaginary component (ε”) of the dielectric constant of the soil/water system [55]. For these these soils, the difference between actual and estimated values by the manufacturer pa- soils, the difference between actual and estimated values by the manufacturer parameters rameters tends to increase as the degree of saturation of soil increases. Soil SB has an iron tends to increase as the degree of saturation of soil increases. Soil S has an iron oxides oxides content of about 6.5% [56] with minor contents of pyrite and chlorite.B As reported Sustainability 2021, 13, 227 11 of 15

content of about 6.5% [56] with minor contents of pyrite and chlorite. As reported by Robinson et al. [57], the iron oxide content, coupled with the length of sensor rods used, play an important role in capacitance probe working at 100 MHz, such as the PR2/6 probe. However, recent research has shown that the effects of iron content are more evident for instruments working at even lower frequencies (cf., a WET sensor working at 50 MHz, [55]). The effects of an accurate calibration are also evident when analyzing the temporal variations of soil water content with depth in the experimental field. The use of the PR2/6 probe without an accurate calibration does not help the understanding of what is really happening in the soil. As shown in Figure6a–d, although the shape of the moisture profiles is the same, there are essential differences between θ values obtained by the calibrated equation and those by the manufacturer one. Referring to Figure6c, the difference between the two soil moisture profiles is exacerbated after rainy periods. Following to 40 mm of rain in three days (from 14 May to 16 May), the hydrogeological processes that occurred in the shallow soil (first 30 cm depth) increased the θ values from about 18% (calibrated parameters) to 27% (manufacturer parameters). In other words, the fraction of water actually occupied by free water into voids is much higher if the manufacturer equation is used. As presented by Haga et al. [58], the subsurface water dynamics also depends on the antecedent soil moisture conditions, which can be evaluated by using the Antecedent Soil moisture Index (ASI). The sum of ASI and precipitation (P) related to different stormflows allows the identification of threshold values (ASI + P, in mm) above which runoff significantly increases [59,60]. In general, the ASI index is estimated at catchment scale or on plot scale by using remote sensing data or indirect methods, such as TDR or capacitance probes: as illustrated, the calibration process is very important in the latter. An overestimation of the soil moisture affects the ASI index computation and therefore, the definition of reliable runoff thresholds. For example, referring to the middle May rainfall event, the ASI index calculated in the first 30 cm depth is 36 or 51 mm depending on whether the calibrated or factory parameters are used. As a result of rainfalls and processes occurring in the shallow soil (runoff, evapotranspiration, etc.), the water gradually infiltrates, producing the decrease of matric suction and the increase of the effective degree of saturation (Se). In detail, Se in the first 30 cm depth is overestimated of about 20 percentage points by using manufacturer parameters (Figure6g ). Although the information was obtained on a small plot, the results are important for soil water management. As Se increases, the soil tends to absorb much less water and thus increases the runoff, with practical implications in different disciplines, including , , , etc. [61]. The comprehension of landscape processes requires quantifying water and sediment fluxes, i.e., through a connectivity- based approach [61]. As illustrated, the antecedent soil moisture content regulates the partitioning of rainfall into infiltration and runoff, even though other components have to be carefully evaluated. As discussed by Zhao et al. [62], at a local scale, micro-relief acts similar to the vegetation cover, reducing the surface wash velocity and increasing the infiltration rate. These aspects are not considered in this paper since it focused on the effect of soil moisture reliability’s estimates. To improve the soil-water management, the concepts discussed in this study should be included. To achieve the SDGs, soil hydraulic properties and soil monitoring need to be assessed, indicating that better measurements and modeling approaches are crucial. According to [63,64], modern technological solutions can provide the needed data and information, but the harmonization of monitoring programs and measurement standards and protocols still needs to be completed. The present work contributes to these topics: good data and sustainable practices contribute in mitigating the land degradation, moving towards a Land Degradation-Neutrality target (LDN), an important goal to increase sustainable [65,66].

5. Conclusions The achieving of sustainable water management requires reliable soil moisture data, which are increasingly obtained by using electromagnetic methods. The laboratory and Sustainability 2021, 13, 227 12 of 15

field-scale investigations provided useful recommendations on the use of the PR2/6 profile probe, and in general capacitance probes working at 100 MHz, to obtain reliable data for the understanding of some processes in the unsaturated zone made by fine-grained soils. The calibration parameters for the different soils considered are useful in various fields of application where the infiltration play a key role (groundwater recharge, erosion and runoff, irrigation, etc.). Particularly interesting is the results for the flyschoid sand (soil SB), which widely outcrops along the Central-Northern Apennines, confirming that the iron content deeply affects the soil moisture estimations. This aspect, which is often not carefully taken into account, inevitably leads to erroneous assessments, impacting the soil water management. After the calibration, the probe, coupled with the modeling of non-saturated parameters, can accurately describe the dynamic of water in soils. In this way, further studies on other types of materials and in different pedoclimatic conditions are needed to implement an effective monitoring network that is useful for managing the soil water and for supporting the validation of remote sensing data and hydrological soil models. The work contributes to the achievement of LDN goals, as electromagnetic tools are becoming increasingly popular in modern agricultural practices of sustainable soil management.

Supplementary Materials: The following are available online at https://www.mdpi.com/2071-105 0/13/1/227/s1. Author Contributions: Conceptualization, L.D.M.; methodology, L.D.M. and S.O.; formal analysis, L.D.M., A.S., and S.O.; investigation, L.D.M., A.S., and S.O.; data curation, L.D.M., and S.O.; writing— original draft preparation, L.D.M. and S.O.; writing—review and editing, L.D.M. and S.O.; funding acquisition, L.D.M. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by Dipartimento di Fisica e Geologia of University of Perugia in the framework of the Project DIMBASE14. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Data are contained in the supplementary material. Acknowledgments: The geotechnical analyses were performed in the Laboratorio di Geologia Ap- plicata of the University of Perugia. The authors are grateful for the technical support of Geosurveys Srl for DPSH tests. We would like to thank the anonymous Reviewers for their useful comments and suggestions. Conflicts of Interest: The authors declare no conflict of interest.

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